Lead data strategy, design scalable data architectures and pipelines, and apply advanced analytics/ML to generate business insights. Mentor teams, collaborate cross-functionally, drive data governance, and use cloud and big data tools to build and visualize data solutions for financial clients.
Key Responsibilities:
- Data Strategy & Architecture:
- Develop and implement data strategies aligned with business objectives.
- Design and maintain scalable, high-performance data architectures and solutions.
- Build and manage data pipelines, integrating data from various sources, ensuring data quality and accessibility.
- Advanced Analytics & Insights:
- Lead the use of advanced analytics, machine learning, and AI to derive insights from large datasets.
- Collaborate with business stakeholders to understand requirements and deliver actionable insights that influence decision-making.
- Design and deploy predictive and prescriptive analytics models to optimize business processes.
- Technical Leadership & Collaboration:
- Mentor junior data engineers and analysts, providing guidance on technical best practices.
- Collaborate with cross-functional teams (IT, business units, data scientists) to identify and resolve data-related challenges.
- Drive the adoption of data governance practices to ensure data integrity, privacy, and compliance.
- Tools & Technology:
- Utilize big data technologies, cloud platforms, and analytics tools (e.g., Hadoop, Spark, Azure, AWS, Power BI, Tableau, Python).
- Develop and optimize complex SQL queries for data extraction and transformation.
- Leverage visualization tools to present data in a clear and concise manner to non-technical stakeholders.
Qualification
- 15+ years of experience in Information Technology with proven track record of delivering high profile projects or managing products.
- Extensive hands-on experience in cloud based data platform technologies including relational and non-relational databases (DynamoDB, Bigtable, Cassandra), data warehouses (Snowflake, RedShift, BigQuery), caching (Redis), data science and machine learning tools, and related programming languages (Python, SAS, SQL)
- Experience with data visualization tools like Tableau or Power BI.
- Hands on experience in building and optimizing data pipelines using technologies like Kafka, Airflow, Spark, Hive, Kubernetes
- Proficient in building and managing data platform in cloud technologies like AWS/GCP
- Ability to assess the code if needed and provide actionable suggestions on designs and implementations.
- Experience in working with financial clients and domain
Compensation, Benefits and Duration
Minimum Compensation: USD 74,000
Maximum Compensation: USD 259,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees.
This position is not available for independent contractors
No applications will be considered if received more than 120 days after the date of this post
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Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
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- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
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- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
